1. Field of the Invention
This invention relates to the general subject of estimating earth, body and material elastic and compositional parameters from seismic or echoacoustic data.
2. Description of the Prior Art
The present invention may be applied to seismic data acquired to analyze the earth subsurface and to echo-acoustic data acquired to analyze human or other mammal bodies and to analyze materials. The discussion of the present invention focuses on application in seismic data analysis of (potential) oil and gas reservoirs. However, the present invention may equally be applied in the analysis of seismic data for other subsurface features of interest and in the analysis of echo-acoustic acquired for medical and material investigation purposes.
Seismic data is acquired to provide information about the subsurface structure, stratigraphy, lithology and fluids contained in the rocks. Acquired seismic data records are the response of a seismic energy source after passing through and being reflected by rocks in the subsurface. Seismic data can be acquired at or close to the earth's surface or can be acquired along boreholes. In most seismic acquisition set-ups each point in the subsurface will have many seismic data measurements associated with it. After acquisition, seismic data is processed to a set of seismic traces, where each trace is associated with a certain surface x,y location. The trace itself consists of a series of samples of the seismic response, usually ordered to correspond to increasing seismic travel time. In this processing the many seismic data measurements at each point will be strongly reduced with the key goal to reduce noise. After processing, one or multiple seismic traces may be associated with each surface x,y location. Dependent on the acquisition geometry, the seismic traces are usually processed and organized to form lines along the surface with regularly spaced traces. The seismic data along such lines can be viewed as sections through the earth. Seismic data is referred to as 2D seismic data when the lines are in different directions or are far apart relative to the spacing of the traces. Seismic data is referred to as 3D seismic data when the acquisition is such that the processing results in a set of seismic lines that are organized sequentially and where the x,y trace locations form a regular grid and such that the spacing of the seismic lines generally is within the same order of magnitude as the spacing of the traces within the lines. In practice, the lines along which the data is acquired are called inlines and lines orthogonal to the inlines are referred to as crosslines.
The amplitude of seismic waves reflecting from a rock boundary change with changing angle of incidence of the incoming seismic waves. These changes with angle can hold valuable information about the types of rocks in the subsurface and fluids they contain. For this reason in modern seismic data processing multiple seismic data sets for analysis and interpretation are routinely generated by processing acquired seismic data to a form where each data set holds different information about the angle dependency of reflection amplitudes. A simple example is of processing the input seismic data to partial angle or offset stacks. In this process, at each trace location, the set of acquired seismic data traces corresponding to a certain angle or offset range are stacked together. When different angle or offset ranges are chosen to generate multiple seismic data sets, information on the changes in seismic amplitude as a function of angle is retained. On the other hand, most of the noise and data reduction advantages of stacking are also retained. There are many other ways to stack data such that multiple data sets are generated which hold information on the angle dependent reflectivity, for example slant stacking and weighted stacking, see e.g. Yilmaz, O., “Seismic data analysis”, Investigations in Geophysics, Society of Exploration Geophysicists, vol. 2, pp. 1807-1839, 1987; Smith, G. C. and Gidlow, P. M., “Weighted stacking for rock property estimation and detection of gas”, Geophysical Prospecting, vol. 35, pp. 993-1014, 1987; and Fatti, J. L., Smith, G. C., Vail, P. J., Strauss, P. J. and Levitt, P. R., “Detection of gas in sandstone reservoirs using AVO analysis: A 3-D seismic case history using the Geostack technique”, Geophysics vol. 59, pp. 1362-1376, 1994. In the following the stacks of any seismic processing method which produces multiple seismic data sets which in some form retain independent information on the change of reflectivity amplitude with angle are referred to as partial stacks. The term full stack is used to describe data obtained by a seismic processing method which at each trace location stacks all input seismic data into a single trace.
In seismic data acquisition pressure wave data using pressure wave sources and receivers sensitive to pressure waves is most commonly acquired. However, other types of seismic data may also be acquired. In so called multi-component data acquisition shear wave data is additionally measured, where the shear waves either originate from shear wave sources or from pressure wave sources. Wave conversion from pressure to shear result in shear waves being generated even when the source generates pressure waves (and vice versa for shear wave sources). These data can also be processed to partial stacks and provide further information about the subsurface. Alternatively, when such data are available and as these data contain different information about the subsurface from the pressure wave data, full stack pressure wave data and full stack shear or converted wave data can also be used in the method or full stack data of one type can be combined with partial stacks of another type. At a minimum, two different full or partial stacks holding different information about the angle dependency of reflection amplitudes are required.
The amplitudes both of pressure, shear and converted wave seismic data are primarily determined by the strength of the reflection of seismic waves at earth layer boundaries. The reflection strength in turn is determined by changes in the elastic parameters of the rocks when going from one layer to the next and the angle of incidence of the seismic waves at the rock layer boundaries, see e.g. Aki, K. and Richards, P. G., “Quantitative seismology”, W. H. Freeman and Co., vol. 1, pp. 153-154, 1979 and Castagna, J. P. and Backus, M. M., “Offset-dependent reflectivity B theory and practice of AVO analysis”, Investigations in Geophysics, Society of Exploration Geophysicists, vol. 8, pp. 3-11, 1993. The elastic parameters are pressure wave velocity, shear wave velocity and density. Alternatively, the elastic parameters may be presented in the form of Lame parameters or in other forms such as pressure wave impedance, shear wave impedance and density. The elastic parameters directly relate to the physical compositional parameters of the rocks which are determined by the physical properties of the rock matrix, i.e. the rock with empty rock pores, and fluids contained in the pores, jointly referred to as ‘compositional parameters’. Changes in the rock matrix can be caused by changes in the lithology (rock mineral composition and build-up). Changes in fluids arise from changes in fluid type: water, oil and gas; or changes in properties of the fluid types see e.g. Castagna and Backus, 1993.
In the literature and in prior patents several methods have been discussed which attempt to utilize the information contained in the change of amplitudes in seismic data with changing angle to determine information about elastic parameters and compositional parameters. U.S. Pat. No. 5,583,825 (Carrazone et al.) provides relevant literature references and discusses prior patents. Where these prior methods utilize inversion to estimate elastic or compositional parameters, they propose to use the full prestack seismic data and propose to also estimate the background velocity trend model as part of the method. These methods are computationally very demanding and complex.
It is an object of the invention to obviate the above mentioned drawbacks of the prior art methods and to provide a relatively simple, fast and robust method for estimating the subsurface parameters.